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Correlation of dengue incidence and rainfall occurrence using wavelet transform for João Pessoa city.

Santos, Celso Augusto Guimarães; Guerra-Gomes, Isabel Cristina; Gois, Bruna Macêdo; Peixoto, Rephany Fonseca; Keesen, Tatjana Souza Lima; da Silva, Richarde Marques.
Sci Total Environ; 647: 794-805, 2019 Jan 10.
Artigo em Inglês | MEDLINE | ID: mdl-30096669
Dengue, a reemerging disease, is one of the most important viral diseases transmitted by mosquitoes. In this study, 55,680 cases of dengue between 2007 and 2015 were reported in Paraíba State, among which, 30% were reported in João Pessoa city, with peaks in 2015, 2011 and 2013. Weather is considered to be a key factor in the temporal and spatial distribution of vector-transmitted diseases. Thus, the relationship between rainfall occurrence and dengue incidences reported from 2007 to 2015 in João Pessoa city, Paraíba State, Brazil, was analyzed by means of wavelet transform, when a frequency analysis of both rainfall and dengue incidence signals was performed. To determine the relationship between rainfall and the incidence of dengue cases, a sample cross correlation function was performed to identify lags in the rainfall and temperature variables that might be useful predictors of dengue incidence. The total rainfall within 90 days presented the most significant association with the number of dengue cases, whereas temperature was not found to be a useful predictor. The correlation between rainfall and the occurrence of dengue cases showed that the number of cases increased in the first few months after the rainy season. Wavelet analysis showed that in addition to the annual frequency presented in both time series, the dengue time series also presented the 3-year frequency from 2010. Cross wavelet analysis revealed that such an annual frequency of both time series was in phase; however, after 2010, it was also possible to observe 45° up phase arrows, which indicated that rainfall in the present year led to an increased dengue incidence the following year. Thus, this approach to analyze surveillance data might be useful for developing public health policies for dengue prevention and control.